Methods to improve the efficiency of confirmatory clinical trials

Abstract

The development of new drugs is increasingly costly and ineffective. Most time and money is accounted for by late-stage clinical trials that aim to confirm the safety and efficacy of the investigated drug. To assure the continued arrival of new and affordable therapies, it is therefore essential to optimize the efficiency and success-rates of these trials. Exploration and implementation of innovative trial methodology is of key importance to achieve this goal. This thesis discusses clinical trial simulation (CTS), adaptive trial designs, and a number of analytical methods for clinical trial data. CTS is a statistical simulation technique to mimic the course of a trial before it is started in order to identify and resolve potential flaws in the study protocol (sub-optimal dosing, insufficient sample size, etc.) and reduce the failure-rate of clinical trials. Numerous adaptive trial designs have been proposed. In this thesis, methodological and statistical properties of several adaptive trial designs are addressed that allow to modify the protocol of an ongoing study based on incoming data as the trial progresses. The analytical methods that are evaluated all aim for the optimal use of the collected information